March 13 - According to a Reuters report, Meta (META, Financial) is quietly testing its first in?house AI training chip in a bid to slash infrastructure costs and challenge Nvidia's (NVDA, Financial) dominance in the AI hardware market. The chip, part of Meta's Training and Inference Accelerator (MTIA) series and manufactured by Taiwan's TSMC, recently completed a crucial tape?out phase, a key early milestone in chip development.
Meta is looking to spend up to $119 billion on AI in 2025, with about $65 billion allocated to AI infrastructure. As it has spent billions on Nvidia GPUs, Meta is now reducing its reliance on external suppliers and trying to optimize its own systems for jobs such as recommendation algorithms and generative AI.
Chief Product Officer Chris Cox described the project as a walk, crawl, run situation, acknowledging past setbacks while highlighting the chip's potential. If successful, Meta plans to fully integrate the chip into its AI training platforms by 2026, potentially reshaping cost structures and altering the competitive landscape in favor of greater AI independence. However, any misstep could result in significant delays and cost overruns.
This article first appeared on GuruFocus.免責聲明：投資有風險，本文並非投資建議，以上內容不應被視為任何金融產品的購買或出售要約、建議或邀請，作者或其他用戶的任何相關討論、評論或帖子也不應被視為此類內容。本文僅供一般參考，不考慮您的個人投資目標、財務狀況或需求。TTM對信息的準確性和完整性不承擔任何責任或保證，投資者應自行研究並在投資前尋求專業建議。